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Mixed phase Fe 2 O 3 /Mn 3 O 4 magnetic nanocomposite for enhanced adsorption of methyl orange dye: Neural network modeling and response surface methodology optimization
Author(s) -
Bhowmik Mahashweta,
Deb Krishna,
Debnath Animesh,
Saha Biswajit
Publication year - 2018
Publication title -
applied organometallic chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.53
H-Index - 71
eISSN - 1099-0739
pISSN - 0268-2605
DOI - 10.1002/aoc.4186
Subject(s) - adsorption , nanocomposite , chemistry , response surface methodology , langmuir adsorption model , methyl orange , magnetic nanoparticles , chemical engineering , central composite design , nuclear chemistry , nanoparticle , analytical chemistry (journal) , chromatography , organic chemistry , catalysis , photocatalysis , engineering
In this research, a novel magnetic mesoporous adsorbent with mixed phase of Fe 2 O 3 /Mn 3 O 4 nanocomposite was prepared by a facile precipitating method and characterized extensively. The prepared nanocomposite was used as adsorbent for toxic methyl orange (MO) dye removal from aqua matrix considering its high surface area (178.27 m 2 /g) with high saturation magnetization (23.07 emu/g). Maximum dye adsorption occurs at solution pH 2.0 and the electrostatic attraction between anionic form of MO dye molecules and the positively charged nanocomposite surface is the main driving force behind this adsorption. Response surface methodology (RSM) was used for optimizing the process variables and maximum MO removal of 97.67% is obtained at optimum experimental condition with contact time, adsorbent dose and initial MO dye concentration of 45 min, 0.87 g/l and 116 mg/l, respectively. Artificial neural network (ANN) model with optimum topology of 3–5–1 was developed for predicting the MO removal (%), which has shown higher predictive ability than RSM model. Maximum adsorption capacity of this nanocomposite was found to be 322.58 mg/g from Langmuir isotherm model. Kinetic studies reveal the applicability of second‐order kinetic model with contribution of intra‐particle diffusion in this process.